I don't usually do these kinds of posts, and I hope that everyone understands my intentions are good here.
But.
In a data deficient landscape like that of #longcovid, one bad data study can create narratives that persist long after new, good data is created. I want to talk 1/
about one of these.
The Kings College symptom tracker is an app. Because they track symptoms over time, it gets a lot of citations on Long Covid prevalence, and also symptom prevalence.
But there are 2 *huge* issues with it:
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1) Because it's an app, it gets exhausting to use, and people stop using it. This is a known and public problem, understood by Tim himself:
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There are so many reasons people stop using it
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More
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2) The other big issue is that the app didn't (possibly still doesn't) collect data on one of the most prevalent symptoms - "brain fog"/cognitive dysfunction - despite requests from patients to do so - despite neurological symptoms generally lasting longer:
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Again, so many requests from patients:
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Tim Spector/team publish those numbers as Long Covid prevalence anyway, & claim that just 1.5% of COVID patients are still symptomatic at 3 months🙃 institute.global/policy/long-co…
There are few official population studies (which is part of the problem)-let's look at what they say:
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docs.google.com/spreadsheets/d…
None come close to 1.5% at 3 months - it's an order of magnitude smaller than other estimates. 10/
And the fact is, you can't put numbers out into the world without explaining the serious biases behind them and then say "take this with a grain of salt." It's been 2 days and these figures have already ended up in the BBC (bbc.com/news/health-54…) 11/
and articles like this one, with King's College team members claiming ""This is absolutely the message we should give: a small proportion have symptoms at 13 weeks, but really pretty much everybody is better by then," Dr Williams said." telegraph.co.uk/global-health/… 12/
These numbers and subsequent narratives are going to be so hard to beat, and they are going to ultimately *HARM* #longcovid patients. As the saying goes "The amount of energy needed to refute bullshit is an order of magnitude bigger than to produce it." 13/
I think Tim Spector is a good person. I'm a huge microbiome nerd and his work there is cool. But this is irresponsible, embarrassing, and needs to be in the public #longcovid awareness, if not corrected completely.
End rant.
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We need an acknowledgment from @KingsCollegeLon@Join_ZOE@timspector on this, and to hear clear feedback on how they are going to change going forward - including how they are going to present their numbers in public. #longcovid care depends on it.
The @Join_ZOE app has now paired with a millionaire's underwear company, so on top of blatantly misrepresenting the most important data (#longcovid prevalence), it's also using patients' #longcovid data for commercial partnerships.
While we had a few thousand more fill in the survey, this paper focuses on 3,762 #longhaulers (sick >28 days) who got sick between Dec-May (to look at an average of ~6 months of data).
Some key findings:
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We looked at 205 symptoms over 10 organs systems (Neuropsychiatric, Pulmonary, Head Ears Eyes Nose Throat (HEENT), Gastrointestinal, Cardiovascular, Musculoskeletal, Immunologic, Dermatologic, Reproductive/Genitourinary/Endocrine).
On average, 9 in 10 of these were affected! 2/
Of the 205 symptoms, we looked at 74 over time, looking at Weeks 1-4 and Months 2-7.
These graphs show the % of respondents who have reached each month who have these symptoms. Some of them go down (fever*, dry cough) while others don't. (*tho some have fever for months!) 3/